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Grooming the Hairball - How to Tidy up Network Visualizations?

Grooming the Hairball - How to Tidy up Network Visualizations?. Hans-Jörg Schulz 1 , Christophe Hurter 2. VIS Tutorial 2013. University of Rostock, Rostock, Germany French Civil Aviation University, ENAC, Toulouse, France. INTRODUCTION. Speakers: Hans-Jörg Schulz & Christophe Hurter.

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Grooming the Hairball - How to Tidy up Network Visualizations?

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  1. Grooming the Hairball - How to Tidy up Network Visualizations? Hans-Jörg Schulz1, Christophe Hurter2 VIS Tutorial 2013 University of Rostock, Rostock, Germany French Civil Aviation University, ENAC, Toulouse, France

  2. INTRODUCTION Speakers: Hans-Jörg Schulz & Christophe Hurter VIS Tutorial: Grooming the Hairball – H.-J. Schulz, C. Hurter

  3. About the Speakers: Hans-Jörg Schulz • PhD in 2010 @ Rostock • Thesis on Graph Visualization • Now PostDoc @ Rostock • Fields of Research: • Design Spaces • Vis. of Heterogeneous Data • Vis. for the Life Sciences • Graph & Tree Visualization VIS Tutorial: Grooming the Hairball – H.-J. Schulz, C. Hurter

  4. About the Speakers: Christophe Hurter • PhD in 2010 @ University of Toulouse • Thesis on Multivariate data exploration • Now Assistant Professor @ ENAC, French Civil Aviation University • Fields of Research: • Multivariate data exploration • GP-GPU techniques • Information visualization • Trajectory exploration VIS Tutorial: Grooming the Hairball – H.-J. Schulz, C. Hurter

  5. About the Tutorial Topic • Node-link diagrams for network data • often attributed to Moreno for depicting social networks [source: Freeman 2000] VIS Tutorial: Grooming the Hairball – H.-J. Schulz, C. Hurter

  6. About the Tutorial Topic • Node-link diagrams for network data • often attributed to Moreno for depicting social networks • but instances of earlier examples exist (e.g., family trees ) that go back as far as the 13th century • (obviously) still hand-drawn back then [source: Kruja et al. 2001] VIS Tutorial: Grooming the Hairball – H.-J. Schulz, C. Hurter

  7. About the Tutorial Topic • Node-link diagrams for network data • often attributed to Moreno for depicting social networks • but instances of earlier examples exist (e.g., family trees ) that go back as far as the 13th century • (obviously) still hand-drawn back then • first automated layout routines appeared in the 1960‘s – e.g., [Tutte 1963] [source: Eades+Hong 2012] VIS Tutorial: Grooming the Hairball – H.-J. Schulz, C. Hurter

  8. About the Tutorial Topic • Classifications of Node-link diagrams • By degrees of freedom of the nodes Free Styled Fixed [adapted from: Schulz+Schumann 2006] VIS Tutorial: Grooming the Hairball – H.-J. Schulz, C. Hurter

  9. About the Tutorial Topic • Classifications of Node-link diagrams • By degrees of freedom of the edges Polyline/Orthogonal Straight Spline Arc [adapted from: Gansner 2013, Dagstuhl talk] VIS Tutorial: Grooming the Hairball – H.-J. Schulz, C. Hurter

  10. About the Tutorial Topic • But, Node-Link-Layouts usually don’t scale! Blog network visualized with Gephi[source: learningfrontiers.eu] E. coli metabolic network visualized with Cytoscape [source: kavrakilab.org] VIS Tutorial: Grooming the Hairball – H.-J. Schulz, C. Hurter

  11. About the Tutorial Topic • A Conceptual Framework to Solve this Problem WHEN? Network Simplification Data Level (Filtering) Geometry Level (Mapping) Image Level(Rendering) Detection Determine where clutter occurs Remove the detected clutterby simplifying the network Reduction HOW? Interaction Interactively refine the result

  12. About the Tutorial Topic • A Conceptual Framework to Solve this Problem WHEN? Network Simplification Data Level (Filtering) Geometry Level (Mapping) Image Level(Rendering) Detection Simplify the network before the actual layout starts Simplify the network during the layout computation Simplify the network after the layout has been generated Reduction HOW? Interaction

  13. About the Tutorial Topic • A Conceptual Framework to Solve this Problem WHEN? Network SimplificationExamples Data Level (Filtering) Geometry Level (Mapping) Image Level(Rendering) Detection Compute DoI values for elements Determine con-fluence of edges Register overplot-ting in each Pixel Contract elements with low DoIs Merge overplotted Pixels into a splat Bundle edges with high pairwise confl. Reduction HOW? Adjust DoI threshold to steer the degree of reduction Use lens to locally un-bundle edges for detailed inspection Adapt the range of influence of the splat function (σ) Interaction

  14. About the Tutorial Structure • Tentative Schedule: • 0. Introduction (you’re listening to it right now)8:30-8:45 (≈ 20 minutes) • Node Set Simplification8:45-10:00 (≈ 70 minutes) • Edge Set Simplification10:00-10:10 (≈ 10 minutes)10:10-10:30 coffee break10:30-11:35 (≈ 65 minutes) • Applications & Open Research Questions11:35-12:10 (≈ 35 minutes) VIS Tutorial: Grooming the Hairball – H.-J. Schulz, C. Hurter

  15. About the Tutorial Structure • If you have remarks or questions pleasefeel free to ask them on the spot! • Download this Slide Deck + the Literature List @ • http://tinyurl.com/tutorial2013 VIS Tutorial: Grooming the Hairball – H.-J. Schulz, C. Hurter

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